Hemant Bhanawat
Founder at falarica
Pune, Maharashtra, India
Summary
🤩
RockstarHemant Bhanawat is a founder and seasoned software engineer with a decade of experience specializing in distributed systems, query processing engines, and high-performance computing. Based in Pune, he combines entrepreneurial drive with deep hands-on backend expertise, notably contributing to SnappyData—a memory-optimized analytics database built on Apache Spark and Geode—where he implemented column-table DDL, indexing, memory manager improvements, and enhanced collocated joins. His strengths lie in architecting scalable analytics infrastructure and container-aware frameworks that bridge streaming, transactional, and analytical workloads. Hemant’s work shows a practical focus on compatibility and performance, including updates to support older Spark versions and careful memory reclamation for Spark RDDs. As co-founder of Falarica Analytics, he pairs product insight with systems-level coding to move prototypes into production-ready services. He brings a pragmatic blend of research-grade systems thinking and startup execution.
10 years of coding experience
Stackoverflow
165reputation
903reached
9answers
0questions
Github Skills (15)
in-memory-database10
spark10
develop10
backend10
memory-database10
sql10
analytics10
scala10
java9
javas9
spark-jobserver6
apache-spark6
snappydata6
yugabytedb6
django6
Programming languages (7)
Github contributions (5)
TIBCOSoftware/snappydata
Oct 2015 - Sep 2017
Project SnappyData - memory optimized analytics database, based on Apache Spark™ and Apache Geode™. Stream, Transact, Analyze, Predict in one cluster
Role in this project:
Back-end Developer
Back-end DeveloperContributions:59 commits, 82 PRs, 304 pushes in 1 year 11 months
Contributions summary:Hemant primarily contributed to the backend logic of the SnappyData memory-optimized analytics database. They added support for creating indexes on column tables, modifying existing index APIs for consistency, and added support for column table DDL and APIs. The user also made changes to the memory manager to free up memory cached by Spark RDDs and enhanced the LocalJoin component to include collocated join cases. Furthermore, the user updated the code to be compatible with older Spark versions.
memorypredictstreammemory-databasetransact
yugabyte/sysbench
Aug 2021 - Jul 2022
Scriptable database and system performance benchmark
Contributions:13 reviews, 7 commits, 22 PRs in 11 months
db2database-accessscriptableperformance-tuningbenchmark
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